A NASDAQ-listed, multinational corporation developing software products and services for the architecture, engineering, construction, and other top industries, is looking for a Data Scientist. The candidate will work on developing customer insights for the products and be responsible for applying quantitative analysis, data mining, and machine learning to build models, usage patterns, and product roadmap recommendations. The company is a global leader in 3D design, engineering, and entertainment software, helping people imagine, design, and create a better world. The selected candidate will collaborate across teams with the product managers, designers, researchers as well as executives and contribute to leading the future of design.
- Work on a variety of problems that seek to better understand how customers use their products and what drives deeper adoption and usage of products
- Apply your quantitative analysis, data mining, and machine learning expertise to building models that make sense of user needs, usage patterns, factors that drive deeper adoption
- Influence product development, strategy, and roadmap prioritization
- Design and implement machine learning pipelines that improve the company’s evidence-based decision-making capabilities
- Tackle complex problems requiring a creative mindset to find innovative and elegant solutions
- Bachelor’s/Master’s degree in Computer Science (or equivalent experience)
- 2+ years of experience with data science practices and machine learning solutions
- Prior experience with SQL or NoSQL databases
- Skilled at Python, Java, or Scala
- Knowledgeable with big data platforms (Hadoop, Spark, or Hive)
- Must possess a passion for designing, analyzing, and deploying machine learning-based solutions
- Good understanding of CS fundamentals, e.g. algorithms and data structures
- Experience in statistical programming tools such as R, Matlab, SAS, etc.
- Experience with data science toolkits like Pandas, Jupyter, scikit-learn, TensorFlow, etc.
- Must be familiar with statistics concepts and analysis, e.g. hypothesis testing, regression, etc.
- Familiarity with Machine Learning techniques, e.g. classification, clustering, regularization, optimization, dimension reduction, etc.
- Experience in handling tools like MLflow, Airflow, Cron, Docker, and Cloud Platforms such as AWS/GCP is a plus
- Good communication skills and ability to explain complex topics to a non-technical audience